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Merge pull request #25564 from mshabunin:cleanup-imgproc-2
imgproc: C-API cleanup, drawContours refactor #25564 Changes: * moved several macros from types_c.h to cvdef.h (assuming we will continue using them) * removed some cases of C-API usage in _imgproc_ module (`CV_TERMCRIT_*` and `CV_CMP_*`) * refactored `drawContours` to use C++ API instead of calling `cvDrawContours` + test for filled contours with holes (case with non-filled contours is simpler and is covered in some other tests) #### Note: There is one case where old drawContours behavior doesn't match the new one - when `contourIdx == -1` (means "draw all contours") and `maxLevel == 0` (means draw only selected contours, but not what is inside). From the docs: > **contourIdx** Parameter indicating a contour to draw. If it is negative, all the contours are drawn. > **maxLevel** Maximal level for drawn contours. If it is 0, only the specified contour is drawn. If it is 1, the function draws the contour(s) and all the nested contours. If it is 2, the function draws the contours, all the nested contours, all the nested-to-nested contours, and so on. This parameter is only taken into account when there is hierarchy available. Old behavior - only one first contour is drawn:  a New behavior (also expected by the test) - all contours are drawn: 
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@ -201,6 +201,14 @@ namespace cv {
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# define CV_ICC __INTEL_COMPILER
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#endif
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#if defined _WIN32
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# define CV_CDECL __cdecl
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# define CV_STDCALL __stdcall
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#else
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# define CV_CDECL
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# define CV_STDCALL
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#endif
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#ifndef CV_INLINE
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# if defined __cplusplus
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# define CV_INLINE static inline
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@ -482,6 +490,7 @@ Cv64suf;
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* Matrix type (Mat) *
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\****************************************************************************************/
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#define CV_MAX_DIM 32
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#define CV_MAT_CN_MASK ((CV_CN_MAX - 1) << CV_CN_SHIFT)
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#define CV_MAT_CN(flags) ((((flags) & CV_MAT_CN_MASK) >> CV_CN_SHIFT) + 1)
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#define CV_MAT_TYPE_MASK (CV_DEPTH_MAX*CV_CN_MAX - 1)
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@ -508,6 +517,13 @@ Cv64suf;
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# define MAX(a,b) ((a) < (b) ? (b) : (a))
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#endif
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/** min & max without jumps */
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#define CV_IMIN(a, b) ((a) ^ (((a)^(b)) & (((a) < (b)) - 1)))
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#define CV_IMAX(a, b) ((a) ^ (((a)^(b)) & (((a) > (b)) - 1)))
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#define CV_SWAP(a,b,t) ((t) = (a), (a) = (b), (b) = (t))
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#define CV_CMP(a,b) (((a) > (b)) - ((a) < (b)))
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#define CV_SIGN(a) CV_CMP((a),0)
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///////////////////////////////////////// Enum operators ///////////////////////////////////////
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/**
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@ -90,13 +90,7 @@
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#include <float.h>
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#endif // SKIP_INCLUDES
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#if defined _WIN32
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# define CV_CDECL __cdecl
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# define CV_STDCALL __stdcall
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#else
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# define CV_CDECL
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# define CV_STDCALL
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#endif
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#ifndef CV_DEFAULT
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# ifdef __cplusplus
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@ -203,21 +197,13 @@ enum {
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* Common macros and inline functions *
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\****************************************************************************************/
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#define CV_SWAP(a,b,t) ((t) = (a), (a) = (b), (b) = (t))
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/** min & max without jumps */
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#define CV_IMIN(a, b) ((a) ^ (((a)^(b)) & (((a) < (b)) - 1)))
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#define CV_IMAX(a, b) ((a) ^ (((a)^(b)) & (((a) > (b)) - 1)))
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/** absolute value without jumps */
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#ifndef __cplusplus
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# define CV_IABS(a) (((a) ^ ((a) < 0 ? -1 : 0)) - ((a) < 0 ? -1 : 0))
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#else
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# define CV_IABS(a) abs(a)
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#endif
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#define CV_CMP(a,b) (((a) > (b)) - ((a) < (b)))
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#define CV_SIGN(a) CV_CMP((a),0)
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#define cvInvSqrt(value) ((float)(1./sqrt(value)))
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#define cvSqrt(value) ((float)sqrt(value))
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@ -675,8 +661,6 @@ CV_INLINE int cvIplDepth( int type )
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#define CV_MATND_MAGIC_VAL 0x42430000
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#define CV_TYPE_NAME_MATND "opencv-nd-matrix"
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#define CV_MAX_DIM 32
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#ifdef __cplusplus
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typedef struct CvMatND CvMatND;
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CV_EXPORTS CvMatND cvMatND(const cv::Mat& m);
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@ -49,8 +49,8 @@ void cv::cornerSubPix( InputArray _image, InputOutputArray _corners,
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const int MAX_ITERS = 100;
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int win_w = win.width * 2 + 1, win_h = win.height * 2 + 1;
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int i, j, k;
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int max_iters = (criteria.type & CV_TERMCRIT_ITER) ? MIN(MAX(criteria.maxCount, 1), MAX_ITERS) : MAX_ITERS;
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double eps = (criteria.type & CV_TERMCRIT_EPS) ? MAX(criteria.epsilon, 0.) : 0;
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int max_iters = (criteria.type & TermCriteria::MAX_ITER) ? MIN(MAX(criteria.maxCount, 1), MAX_ITERS) : MAX_ITERS;
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double eps = (criteria.type & TermCriteria::EPS) ? MAX(criteria.epsilon, 0.) : 0;
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eps *= eps; // use square of error in comparison operations
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cv::Mat src = _image.getMat(), cornersmat = _corners.getMat();
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@ -39,6 +39,7 @@
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//
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//M*/
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#include "precomp.hpp"
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using namespace cv;
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namespace cv
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{
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@ -2468,35 +2469,6 @@ void cv::polylines(InputOutputArray img, InputArrayOfArrays pts,
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polylines(img, (const Point**)ptsptr, npts, (int)ncontours, isClosed, color, thickness, lineType, shift);
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}
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namespace
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{
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using namespace cv;
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static void addChildContour(InputArrayOfArrays contours,
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size_t ncontours,
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const Vec4i* hierarchy,
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int i, std::vector<CvSeq>& seq,
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std::vector<CvSeqBlock>& block)
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{
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for( ; i >= 0; i = hierarchy[i][0] )
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{
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Mat ci = contours.getMat(i);
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cvMakeSeqHeaderForArray(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
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!ci.empty() ? (void*)ci.ptr() : 0, (int)ci.total(),
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&seq[i], &block[i] );
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int h_next = hierarchy[i][0], h_prev = hierarchy[i][1],
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v_next = hierarchy[i][2], v_prev = hierarchy[i][3];
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seq[i].h_next = (0 <= h_next && h_next < (int)ncontours) ? &seq[h_next] : 0;
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seq[i].h_prev = (0 <= h_prev && h_prev < (int)ncontours) ? &seq[h_prev] : 0;
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seq[i].v_next = (0 <= v_next && v_next < (int)ncontours) ? &seq[v_next] : 0;
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seq[i].v_prev = (0 <= v_prev && v_prev < (int)ncontours) ? &seq[v_prev] : 0;
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if( v_next >= 0 )
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addChildContour(contours, ncontours, hierarchy, v_next, seq, block);
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}
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}
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}
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void cv::drawContours( InputOutputArray _image, InputArrayOfArrays _contours,
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int contourIdx, const Scalar& color, int thickness,
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@ -2504,83 +2476,99 @@ void cv::drawContours( InputOutputArray _image, InputArrayOfArrays _contours,
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int maxLevel, Point offset )
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{
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CV_INSTRUMENT_REGION();
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Mat image = _image.getMat(), hierarchy = _hierarchy.getMat();
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CvMat _cimage = cvMat(image);
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size_t ncontours = _contours.total();
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size_t i = 0, first = 0, last = ncontours;
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std::vector<CvSeq> seq;
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std::vector<CvSeqBlock> block;
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if( !last )
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CV_Assert( thickness <= MAX_THICKNESS );
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const size_t ncontours = _contours.total();
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if (!ncontours)
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return;
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CV_Assert(ncontours <= (size_t)std::numeric_limits<int>::max());
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if (lineType == cv::LINE_AA && _image.depth() != CV_8U)
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lineType = 8;
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Mat image = _image.getMat(), hierarchy = _hierarchy.getMat();
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seq.resize(last);
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block.resize(last);
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for( i = first; i < last; i++ )
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seq[i].first = 0;
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if( contourIdx >= 0 )
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if (thickness >= 0) // contour lines
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{
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CV_Assert( 0 <= contourIdx && contourIdx < (int)last );
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first = contourIdx;
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last = contourIdx + 1;
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}
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for( i = first; i < last; i++ )
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{
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Mat ci = _contours.getMat((int)i);
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if( ci.empty() )
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continue;
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int npoints = ci.checkVector(2, CV_32S);
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CV_Assert( npoints > 0 );
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cvMakeSeqHeaderForArray( CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
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ci.ptr(), npoints, &seq[i], &block[i] );
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}
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if( hierarchy.empty() || maxLevel == 0 )
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for( i = first; i < last; i++ )
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double color_buf[4] {};
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scalarToRawData(color, color_buf, _image.type(), 0 );
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int i = 0, end = (int)ncontours;
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if (contourIdx >= 0)
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{
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seq[i].h_next = i < last-1 ? &seq[i+1] : 0;
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seq[i].h_prev = i > first ? &seq[i-1] : 0;
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i = contourIdx;
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end = i + 1;
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}
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else
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{
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size_t count = last - first;
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CV_Assert(hierarchy.total() == ncontours && hierarchy.type() == CV_32SC4 );
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const Vec4i* h = hierarchy.ptr<Vec4i>();
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if( count == ncontours )
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for (; i < end; ++i)
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{
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for( i = first; i < last; i++ )
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Mat cnt = _contours.getMat(i);
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if (cnt.empty())
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continue;
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const int npoints = cnt.checkVector(2, CV_32S);
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CV_Assert(npoints > 0);
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for (int j = 0; j < npoints; ++j)
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{
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int h_next = h[i][0], h_prev = h[i][1],
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v_next = h[i][2], v_prev = h[i][3];
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seq[i].h_next = (size_t)h_next < count ? &seq[h_next] : 0;
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seq[i].h_prev = (size_t)h_prev < count ? &seq[h_prev] : 0;
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seq[i].v_next = (size_t)v_next < count ? &seq[v_next] : 0;
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seq[i].v_prev = (size_t)v_prev < count ? &seq[v_prev] : 0;
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const bool isLastIter = j == npoints - 1;
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const Point pt1 = cnt.at<Point>(j);
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const Point pt2 = cnt.at<Point>(isLastIter ? 0 : j + 1);
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cv::ThickLine(image, pt1 + offset, pt2 + offset, color_buf, thickness, lineType, 2, 0);
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}
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}
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}
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else // filled polygons
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{
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int i = 0, end = (int)ncontours;
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if (contourIdx >= 0)
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{
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i = contourIdx;
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end = i + 1;
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}
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std::vector<int> indexesToFill;
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if (hierarchy.empty() || maxLevel == 0)
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{
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for (; i != end; ++i)
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indexesToFill.push_back(i);
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}
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else
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{
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int child = h[first][2];
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if( child >= 0 )
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std::stack<int> indexes;
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for (; i != end; ++i)
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{
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addChildContour(_contours, ncontours, h, child, seq, block);
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seq[first].v_next = &seq[child];
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// either all from the top level or a single contour
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if (hierarchy.at<Vec4i>(i)[3] < 0 || contourIdx >= 0)
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indexes.push(i);
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}
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while (!indexes.empty())
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{
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// get current element
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const int cur = indexes.top();
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indexes.pop();
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// check current element depth
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int curLevel = -1;
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int par = cur;
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while (par >= 0)
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{
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par = hierarchy.at<Vec4i>(par)[3]; // parent
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++curLevel;
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}
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if (curLevel <= maxLevel)
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{
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indexesToFill.push_back(cur);
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}
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int next = hierarchy.at<Vec4i>(cur)[2]; // first child
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while (next > 0)
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{
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indexes.push(next);
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next = hierarchy.at<Vec4i>(next)[0]; // next sibling
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}
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}
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}
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std::vector<Mat> contoursToFill;
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for (const int & idx : indexesToFill)
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contoursToFill.push_back(_contours.getMat(idx));
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fillPoly(image, contoursToFill, color, lineType, 0, offset);
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}
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cvDrawContours( &_cimage, &seq[first], cvScalar(color), cvScalar(color), contourIdx >= 0 ?
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-maxLevel : maxLevel, thickness, lineType, cvPoint(offset) );
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}
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static const int CodeDeltas[8][2] =
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{ {1, 0}, {1, -1}, {0, -1}, {-1, -1}, {-1, 0}, {-1, 1}, {0, 1}, {1, 1} };
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@ -389,14 +389,14 @@ static void initGMMs( const Mat& img, const Mat& mask, GMM& bgdGMM, GMM& fgdGMM
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int num_clusters = GMM::componentsCount;
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num_clusters = std::min(num_clusters, (int)bgdSamples.size());
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kmeans( _bgdSamples, num_clusters, bgdLabels,
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TermCriteria( CV_TERMCRIT_ITER, kMeansItCount, 0.0), 0, kMeansType );
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TermCriteria( TermCriteria::MAX_ITER, kMeansItCount, 0.0), 0, kMeansType );
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}
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{
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Mat _fgdSamples( (int)fgdSamples.size(), 3, CV_32FC1, &fgdSamples[0][0] );
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int num_clusters = GMM::componentsCount;
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num_clusters = std::min(num_clusters, (int)fgdSamples.size());
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kmeans( _fgdSamples, num_clusters, fgdLabels,
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TermCriteria( CV_TERMCRIT_ITER, kMeansItCount, 0.0), 0, kMeansType );
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TermCriteria( TermCriteria::MAX_ITER, kMeansItCount, 0.0), 0, kMeansType );
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}
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bgdGMM.initLearning();
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@ -651,7 +651,7 @@ cv::Moments cv::moments( InputArray _src, bool binary )
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if( binary )
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{
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cv::Mat tmp(tileSize, CV_8U, nzbuf);
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cv::compare( src, 0, tmp, CV_CMP_NE );
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cv::compare( src, 0, tmp, cv::CMP_NE );
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src = tmp;
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}
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@ -61,6 +61,7 @@
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#include <stdio.h>
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#include <limits.h>
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#include <float.h>
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#include <stack>
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#define GET_OPTIMIZED(func) (func)
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@ -373,11 +373,11 @@ void cv::pyrMeanShiftFiltering( InputArray _src, OutputArray _dst,
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if( src0.size() != dst0.size() )
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CV_Error( cv::Error::StsUnmatchedSizes, "The input and output images must have the same size" );
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if( !(termcrit.type & CV_TERMCRIT_ITER) )
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if( !(termcrit.type & TermCriteria::MAX_ITER) )
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termcrit.maxCount = 5;
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termcrit.maxCount = MAX(termcrit.maxCount,1);
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termcrit.maxCount = MIN(termcrit.maxCount,100);
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if( !(termcrit.type & CV_TERMCRIT_EPS) )
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if( !(termcrit.type & TermCriteria::EPS) )
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termcrit.epsilon = 1.f;
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termcrit.epsilon = MAX(termcrit.epsilon, 0.f);
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@ -289,7 +289,7 @@ int CV_FindContourTest::validate_test_results( int /*test_case_idx*/ )
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{
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int code = cvtest::TS::OK;
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cvCmpS( img[0], 0, img[0], CV_CMP_GT );
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cvCmpS( img[0], 0, img[0], cv::CMP_GT );
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if( count != count2 )
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{
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@ -1956,12 +1956,6 @@ int CV_ContourMomentsTest::validate_test_results( int test_case_idx )
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if( code < 0 )
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{
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#if 0
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cvCmpS( img, 0, img, CV_CMP_GT );
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cvNamedWindow( "test", 1 );
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cvShowImage( "test", img );
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cvWaitKey();
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#endif
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ts->set_failed_test_info( code );
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}
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@ -928,4 +928,111 @@ TEST(Drawing, circle_memory_access)
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cv::circle(matrix, cv::Point(-1, -1), 0, kBlue, 2, 8, 16);
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}
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inline static Mat mosaic2x2(Mat &img)
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{
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const Size sz = img.size();
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Mat res(sz * 2, img.type(), Scalar::all(0));
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img.copyTo(res(Rect(Point(0, 0), sz)));
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img.copyTo(res(Rect(Point(0, sz.height), sz)));
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img.copyTo(res(Rect(Point(sz.width, 0), sz)));
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img.copyTo(res(Rect(Point(sz.width, sz.height), sz)));
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return res;
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}
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TEST(Drawing, contours_filled)
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{
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const Scalar white(255);
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const Scalar black(0);
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const Size sz(100, 100);
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Mat img(sz, CV_8UC1, black);
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rectangle(img, Point(20, 20), Point(80, 80), white, -1);
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rectangle(img, Point(30, 30), Point(70, 70), black, -1);
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rectangle(img, Point(40, 40), Point(60, 60), white, -1);
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img = mosaic2x2(img);
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Mat img1(sz, CV_8UC1, black);
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rectangle(img1, Point(20, 20), Point(80, 80), white, -1);
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img1 = mosaic2x2(img1);
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Mat img2(sz, CV_8UC1, black);
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||||
rectangle(img2, Point(20, 20), Point(80, 80), white, -1);
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||||
rectangle(img2, Point(30, 30), Point(70, 70), black, -1);
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||||
img2 = mosaic2x2(img2);
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||||
|
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Mat img3(sz, CV_8UC1, black);
|
||||
rectangle(img3, Point(40, 40), Point(60, 60), white, -1);
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img3 = mosaic2x2(img3);
|
||||
|
||||
// inverted contours - corners and left edge adjusted
|
||||
Mat imgi(sz, CV_8UC1, black);
|
||||
rectangle(imgi, Point(29, 29), Point(71, 71), white, -1);
|
||||
rectangle(imgi, Point(41, 41), Point(59, 59), black, -1);
|
||||
imgi.at<uchar>(Point(29, 29)) = 0;
|
||||
imgi.at<uchar>(Point(29, 71)) = 0;
|
||||
imgi = mosaic2x2(imgi);
|
||||
|
||||
vector<vector<Point>> contours;
|
||||
vector<Vec4i> hierarchy;
|
||||
findContours(img, contours, hierarchy, RETR_TREE, CHAIN_APPROX_NONE);
|
||||
ASSERT_EQ(12u, contours.size());
|
||||
|
||||
// NOTE:
|
||||
// assuming contour tree has following structure (idx = 0, 1, ...):
|
||||
// idx (top level)
|
||||
// - idx + 1
|
||||
// - idx + 2
|
||||
// idx + 3 (top level)
|
||||
// - idx + 4
|
||||
// - idx + 5
|
||||
// ...
|
||||
const vector<int> top_contours {0, 3, 6, 9};
|
||||
{
|
||||
// all contours
|
||||
Mat res(img.size(), CV_8UC1, Scalar::all(0));
|
||||
drawContours(res, contours, -1, white, -1, cv::LINE_8, hierarchy);
|
||||
EXPECT_LT(cvtest::norm(img, res, NORM_INF), 1);
|
||||
}
|
||||
{
|
||||
// all contours
|
||||
Mat res(img.size(), CV_8UC1, Scalar::all(0));
|
||||
drawContours(res, contours, -1, white, -1, cv::LINE_8, hierarchy, 3);
|
||||
EXPECT_LT(cvtest::norm(img, res, NORM_INF), 1);
|
||||
}
|
||||
{
|
||||
// all contours
|
||||
Mat res(img.size(), CV_8UC1, Scalar::all(0));
|
||||
drawContours(res, contours, -1, white, -1, cv::LINE_8, hierarchy, 0);
|
||||
EXPECT_LT(cvtest::norm(img, res, NORM_INF), 1);
|
||||
}
|
||||
{
|
||||
// all external contours one by one
|
||||
Mat res(img.size(), CV_8UC1, Scalar::all(0));
|
||||
for (int idx : top_contours)
|
||||
drawContours(res, contours, idx, white, -1, cv::LINE_8, hierarchy, 0);
|
||||
EXPECT_LT(cvtest::norm(img1, res, NORM_INF), 1);
|
||||
}
|
||||
{
|
||||
// all external contours + 1-level deep hole (one by one)
|
||||
Mat res(img.size(), CV_8UC1, Scalar::all(0));
|
||||
for (int idx : top_contours)
|
||||
drawContours(res, contours, idx, white, -1, cv::LINE_8, hierarchy, 1);
|
||||
EXPECT_LT(cvtest::norm(img2, res, NORM_INF), 1);
|
||||
}
|
||||
{
|
||||
// 2-level deep contours
|
||||
Mat res(img.size(), CV_8UC1, Scalar::all(0));
|
||||
for (int idx : top_contours)
|
||||
drawContours(res, contours, idx + 2, white, -1, cv::LINE_8, hierarchy);
|
||||
EXPECT_LT(cvtest::norm(img3, res, NORM_INF), 1);
|
||||
}
|
||||
{
|
||||
// holes become inverted here, LINE_8 -> LINE_4
|
||||
Mat res(img.size(), CV_8UC1, Scalar::all(0));
|
||||
for (int idx : top_contours)
|
||||
drawContours(res, contours, idx + 1, white, -1, cv::LINE_4, hierarchy);
|
||||
EXPECT_LT(cvtest::norm(imgi, res, NORM_INF), 1);
|
||||
}
|
||||
}
|
||||
|
||||
}} // namespace
|
||||
|
Loading…
Reference in New Issue
Block a user